Start by clarifying the problem constraints (e.g., data size, memory limits, whether the list can be modified) and then propose a solution using a hash set to track seen elements while building the output list. Discuss time and space complexity, and mention alternative approaches if constraints differ.
Pro tip: Mention that in Python, you can use a dictionary to preserve order (since Python 3.7) or an OrderedDict for older versions, but explicitly using a set is more memory-efficient and demonstrates deeper understanding. Also, consider edge cases like empty list or all duplicates.
Ask about input size, memory constraints, whether the list can be modified in-place, and if the output should be a new list or modified original.
Use a set to track seen elements and a list to store the result, iterating through the input once. This preserves order and runs in O(n) time.
State that time complexity is O(n) and space complexity is O(n) due to the set and output list. Mention that if memory is tight, sorting could be used but would lose order.
Mention that using a dictionary (or OrderedDict) also works but may have slightly higher overhead. If the list is sorted, a two-pointer approach could work in O(n) time and O(1) extra space, but order is not preserved.
Consider empty list, single element, all duplicates, and non-hashable elements (if applicable). Also, discuss if the input is a stream or very large, requiring a different approach.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Clarify the overlap rule: the last character of the current merged string must match the first character of the next word, and if multiple overlaps are possible, choose the longest overlap to avoid losing characters. Then implement a greedy algorithm that iterates through the list, merging each word by finding the maximum overlap with the current result. Discuss edge cases like no overlap, empty list, and single word.
Pro tip: Always confirm with the interviewer whether the overlap should be the longest possible or just the first match, as this ambiguity can drastically change the output. Also, mention that you would test with words that have multiple overlapping characters (e.g., 'aaa' and 'aaab') to ensure correctness.
Ask about the overlap rule: should it be the longest overlap? What if multiple overlaps exist? Also consider empty list, single word, and words with no overlap.
Use a greedy approach: start with the first word as the result. For each subsequent word, find the maximum k such that the last k characters of the result match the first k characters of the word, then append the word without its first k characters.
Write code to compute the overlap efficiently (e.g., using string slicing or KMP for large inputs). Test with examples like ['abc','rgn','ctr'] and edge cases like ['a','a','a'].
Discuss time complexity: naive overlap check is O(n*m) per merge, but can be optimized. Mention potential improvements if needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.